When Continuous Delivery Is Not an Option: Practical Paths to Continuous Engineering in Complex Organizations
November 04, 2025 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Eriks Klotins, Magnus Ahlgren, Nicolas Martin Vivaldi, Even-Andre Karlsson
arXiv ID
2511.02445
Category
cs.SE: Software Engineering
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Purpose: Continuous Software Engineering (CSE) promises improved efficiency, quality, and responsiveness in software-intensive organizations. However, fully adopting CSE is often constrained by complex products, legacy systems, organizational inertia, and regulatory requirements. In this paper, we examine four industrial cases from the automation, automotive, retail, and chemical sectors to explore how such constraints shape CSE adoption in practice. Methods: We apply and extend a previously proposed CSE Industry Readiness Model to assess the current and potential levels of adoption in each case. Through expert interviews and narrative synthesis, we identify common driving forces and adoption barriers, including organizational preparedness, cross-organizational dependencies, and limited customer demand for continuous delivery. Results: Based on our findings, we propose an updated readiness model that introduces additional levels of internal and external feedback, distinguishes market- and organization-facing constraints, and better guides practitioners in setting realistic CSE adoption goals. Conclusions: Our results highlight that while full end-to-end CSE adoption may not always be feasible, meaningful internal improvements are still possible and beneficial. This study provides empirically grounded guidance for organizations navigating partial or constrained CSE transformations.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted